| met.diameter | R Documentation | 
Calculates the network diameter .
met.diameter(
  M,
  df = NULL,
  weighted = TRUE,
  shortest.weight = FALSE,
  normalization = TRUE,
  directed = TRUE,
  out = TRUE
)
M | 
 a square adjacency matrix, or a list of square adjacency matrices, or an output of ANT functions stat.ds.grp, stat.df.focal, stat.net.lk.  | 
df | 
 a data frame of same length as the input matrix or a list of data frames if argument M is a list of matrices or an output of ANT functions stat.ds.grp, stat.df.focal, stat.net.lk.  | 
weighted | 
 if FALSE, it binarizes the square adjacency matrix M. Geodesic distances and diameter are based only on the presence or absence of edges.  | 
shortest.weight | 
 if false, it considers the highest met.strength as the shortest path.  | 
normalization | 
 normalizes the weights of the links i.e. divides them by the average strength of the network. Argument normalization can't be TRUE when argument weighted is FALSE.  | 
directed | 
 if false, then it symmetrizes the matrix. Otherwise, it calculates geodesic distances and diameter according to the directionality of the links.  | 
out | 
 if true, it considers outgoing ties.  | 
Diameter is the longer geodesic distance.
a double representing the diameter of the network if argument M is a square matrix.
A list of doubles if argument M is a list of matrices and if argument df is NULL. Each double represents the diameter of the corresponding matrix of the list.
A list of arguments df with a new column of network diameter if argumentdf is not NULL and if argument M is a list of matrices. The name of the column is adapted according to arguments values .weighted, shortest.weight, normalization, directed and out.
A list of arguments df with a new column of network diameter if argument df is not NULL, if argument M is an output from ANT functions stat.ds.grp, stat.df.focal, stat.net.lk for multiple matrices permutations, and if argument df is a list of data frames of same length as argument M.
Sebastian Sosa, Ivan Puga-Gonzalez.
Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social networks, 32(3), 245-251.
Sosa, S. (2018). Social Network Analysis, in: Encyclopedia of Animal Cognition and Behavior. Springer.
met.diameter(sim.m)
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